 |
| Titel |
Obstacles and benefits of the implementation of a reduced-rank smoother with a high resolution model of the tropical Atlantic Ocean |
| VerfasserIn |
N. Freychet, E. Cosme, P. Brasseur, J.-M. Brankart, E. Kpemlie |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1812-0784
|
| Digitales Dokument |
URL |
| Erschienen |
In: Ocean Science ; 8, no. 5 ; Nr. 8, no. 5 (2012-09-18), S.797-811 |
| Datensatznummer |
250005870
|
| Publikation (Nr.) |
 copernicus.org/os-8-797-2012.pdf |
|
|
|
|
|
| Zusammenfassung |
| Most of oceanographic operational centers use three-dimensional data
assimilation schemes to produce reanalyses. We investigate here the benefits
of a smoother, i.e. a four-dimensional formulation of statistical
assimilation. A square-root sequential smoother is implemented with a
tropical Atlantic Ocean circulation model. A simple twin experiment is
performed to investigate its benefits, compared to its corresponding filter.
Despite model's non-linearities and the various approximations used for its
implementation, the smoother leads to a better estimation of the ocean state,
both on statistical (i.e. mean error level) and dynamical points of view, as
expected from linear theory. Smoothed states are more in phase with the
dynamics of the reference state, an aspect that is nicely illustrated with
the chaotic dynamics of the North Brazil Current rings. We also show that the
smoother efficiency is strongly related to the filter configuration. One of
the main obstacles to implement the smoother is then to accurately estimate
the error covariances of the filter. Considering this, benefits of the
smoother are also investigated with a configuration close to situations that
can be managed by operational center systems, where covariances matrices are
fixed (optimal interpolation). We define here a simplified smoother scheme,
called half-fixed basis smoother, that could be implemented with current
reanalysis schemes. Its main assumption is to neglect the propagation of the
error covariances matrix, what leads to strongly reduce the cost of
assimilation. Results illustrate the ability of this smoother to provide a
solution more consistent with the dynamics, compared to the filter. The
smoother is also able to produce analyses independently of the observation
frequency, so the smoothed solution appears more continuous in time,
especially in case of a low frenquency observation network. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|